July 2007 Volume 10 Number 3 - Educational Technology & Society

A true, precise and valid model
“Fidelity” is defined as “the degree of similarity between the training situation and the operational situation which is
simulated.” It is a two dimensional measurement of this similarity in terms of : (1) the physical characteristics, for
example visual, spatial, kinesthetic, etc ; and (2) the functional characteristics, for example the informational,
stimulus, and response options of training situation”. (Hay & Singer, 1989: 50). Garris et al (2002) add to that
definition “structural validity”, i.e. processes which appear in the simulation, as well as its value in predicting reality
given the degree of psychological realism in the simulation. From the point of view of learning, Claudet (1998) states
that simulations reproduce situations, dilemmas and actors who participate in them as realistically as possible in
order to provide learners with the opportunity to put into practice and to transfer their experience in a "quasi-real"
situation.
The notion of validity refers to the degree of uniformity and coherence in the environment specifications in
comparaison to reality (Garris et al, 2002). Pedgen et al (1995) state that results obtained by simulations have to be
the same as those obtained in the real world with the system serving as a model for the simulation. Although
simplified, the model must be precise because the essential function of a simulation is to provide users with a better
understanding of reality. This is particularly important in the case of an educational simulation. The notion of
precision with which the model represents reality is closely connected to an earlier introduced notion, that of the
simplification of reality. Indeed, the simpler a model is, the more it runs the risk of distorting the reality under study.
In order to choose the characteristics stemming from the reality which are to be included in the model, the simulation
designer thereby has to determine which phenomena will be reproduced with precision.
Educational character and its potential in helping understanding of the model-related reality
Research in education (including continuing education) has demonstrated that simulations promote competency
development, both basic and complex. For instance, the level of competency required by medical professionals is
better acquired in an environment which uses varied examples in a realistic context and which provides educational
activities of situations which imitate the real world (Demediatris et al, 1999; Swanson et Ornelas, 2001; Zhu, Zhou &
Yin, 2001). Simulations are particularly appropriate in producing such environments because they offer high-level
interactivity, strengthen concept and theory acquisistion and place objects or systems within the center of learning
(Johnson et al, 1998; Charrière & Magnin, 1998).
Regardless of the type or size of simulation used, Milrad (2002) asserts that the main purpose of simulations remains
the offering of an environment: (1) which promotes the development of mental models in learners; (2) which allows
for efficiency testing of the models used to explain or to predict events in a system, and (3) which optimalises the
discovery of the relationships between variables and the confrontation of divergent approaches. Goldenberg et al
(2005) and Hung et al (2005) reached similar conclusions as Milrad (2002) in relation to this last objective (3).
Schnotz et Rasch (2005: 48) consider that the educational character of simulations includes two types of functions
that are based on a decrease in the cognitive load: enabling function and facilitating function. Enabling function: “If
they reduce the cognitive load of tasks in order to allow cognitive processing that would otherwise be impossible,
then animations have an enabling function”. Facilitating function: “If they reduce the cognitive load of tasks that
could otherwise be solved only with high mental effort, then animations have a facilitating function.”
In short, the literature allowed us to reassert that simulation is a simplified, dynamic and precise representation of
reality defined as a system.
Conclusion
Our study focused on the conceptual foundations and distinguishing features of games and simulations. Besides
establishing this differentiation, we addressed the essential attributes of operational definitions of these two concepts:
games and simulations. By essential attributes, we mean the features that are indispensable and common to all
activities that quality as a game or a simulation.
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